In natural zooplankton samples, the intensity of staining specimens with vital dyes varies significantly and, as a result, it is difficult to classify poorly stained organisms exactly to either аlive or dead. If the fraction of the ‘questionable’ organisms in the sample is high, it is impossible to obtain reliable and reproducible results. In this work, a solution of the problem is considered, which is an advanced approach for identifying live/dead organisms in stained samples of mesozooplankton through digitizing their images, averaging their colour (hue) and brightness and, finally, applying discriminant analysis of the colour data obtained for every specimen to classify the latter as live or dead.

Some details and illustrations:

Clusters of NR- (top graphs) and FDA-stained (bottom graphs) live (L) and dead (D) specimens of C. aquaedulcis of different development stages (N – nauplii, C – copepodits, A – adults) in the space of the colour variables. Cluster borders are presented by dashed lines

Scatterplots of the first two canonical discriminant functions derived from discriminant analysis of NR- (НК, top plots) and FDA-stained (ДФ, bottom plots) live (L) and dead (D) copepods C. aquaedulcis when using developmental stage (N – nauplii, C – copepodits, A – adults) as classification factor

NR- (top plots) and FDA-stained (bottom plots) natural copepods classified visually to live (L), dead (D) and questionable (Q) in the space of the colour variables. Right plots represent the results of discriminant analysis: Q-specimens have been classified to L or D (black symbols)